Branch: master
Find file Copy path
Fetching contributors…
Cannot retrieve contributors at this time
123 lines (93 sloc) 6.01 KB
title tags sticky
RStudio Server

SESYNC provides access to a remote RStudio session, via a web browser, in order to work in R while directly connected to other SESYNC resources (file storage, databases, the cluster, etc).


Access RStudio by pointing any web browser to and logging in with your SESYNC username and password. If you forgot your username or password, please go to If your SESYNC credentials do not give you RStudio access, please email {{ }} and ask to enable this resource for your account or whole team.

Running RSudio

Once you log in, you will see an RStudio desktop like application. This RStudio Server application works almost identically to the desktop version. To learn how to use all the features of the RStudio IDE, check out the cheatsheet

R Packages

User contributed R packages can be installed on RStudio either through the menu or the R console. From the menu choose Tools -> Install Packages; from the R console use the install.packages function. If you receive and error saying the package cannot be installed there is a chance some underlying system library is not installed. Please email the error message to {{ }}, and explain which package you need to install.

Where should I save stuff?

"Stuff" usually belongs in one of three places:

  1. Research Home Directory (~/ or equivalently /research-home/USERNAME/).
  2. Research Data Directory (/nfs/PROJECTNAME-data)
  3. Version controlled project (e.g. on GitLab and cloned into ~/)

Research Home Directory

When you first open R studio, you will be working in your home directory which is located at "/research-home/USERNAME" or equivalently "~/". This is a private directory, and only you have access to the files in it. We strongly recommend that you save source code in to your home directory. This will protect against multiple group members attempting to update a project file at the same time. If you need to share code between project members please see 'Version Controlled Project' below.

Research Data Directory

If you've requested it your group will have a data directory available. Your research data directory appears on as PROJECTNAME-data, where PROJECTNAME is the short name assigned for your project by SESYNC IT staff, and is accessed from at the path /nfs/PROJECTNAME-data. You can add to this directory either by saving output from R to folders there, or by using one of the options for uploading described under [How do I access my research data directory?]({{ '/faq/how-do-i-navigate-sesync-storage.html' | relative_url }}). You should store all shared data here. Examples of data types that should be placed here include csv files, landsat imagery, hdf5 data files--anything that's not code that you will be sharing with your group members.

Version Controlled Project

We strongly support using version control to manage work with collaborators, not to mention keeping up with principles of reproducible research. SESYNC provides a free GitLab cloud service for private repositories for pre-release projects. Please see [Creating a new Git Project]({{ '/quickstart/creating-a-new-git-project.html' | relative_url }}) for more information on using this service.

To work with version control systems in RStudio, you create an RStudio "project" to pair with a remote repository.

  1. Go to File -> New Project in RStudio

  2. Choose the type of project:

    • Use Version Control if a remote repository for the project is already populated with files, and be ready to provide the URL (e.g. "").

    • Use Existing Directory if you already have a folder containing only this project's files. Once the project exits, go to Project Options -> GitSVN to choose Git for version control, and be ready to provide the URL (e.g. "").

    • If you don't have files organized into a folder (or are starting from scratch), start by Creating a new Git Project and go back to Step 1.

  3. Move files into the project directory and add them to a commit.

Dealing with Data

Since everyone will be working off of the same set of code, there are three options for working with data. If your data is quite small (i.e. a csv with a few hundred rows, also known as "small-batch artisinal data") you can include it in your project, push it to your remote repository, and everyone will have a clone. Larger datasets should be in your [Research Data Directory]({{ '/quickstart/research-data-directory.html' | relative_url }}) so that everyone is able to work off one shared copy of the data. Very large datasets may need to be loaded into a RDBMS, and SESYNC provides both MySQL and PostgreSQL servers for this purpose. See our FAQ on [Database connections from RStudio]({{ '/faq/Connecting-RStudio-to-Database.html' | relative_url }}) or read the following example of shared file usage.

Let's assume that J. Smith (with USERNAME "jsmith") is part of the "Trees and Urban Heat Island Mitigation" working group. When J. Smith logs in to, the directory "cooltrees-data" will indicate that the PROJECTNAME mentioned above is cooltrees. After uploading the file "urbanET.tif", any member of the project has access to the imagery from RStudio. For example, a script saved as "~/cool-viz.R" could include

urbanET <- raster("/nfs/cooltrees-data/urbanET.tif")

To make the code more portable (i.e. remove the explicit path to a SESYNC research data directory), J. Smith could create a shortcut with the R command file.symlink('/nfs/cooltrees-data', 'data'), and modify the "cool-viz.R" script to use the shortcut:

urbanET <- raster("data/urbanET.tif")